The Floodwater Depth Estimation Tool (FwDET v2.0) for improved remote sensing analysis of coastal flooding

Abstract

Remote sensing analysis is routinely used to map flooding extent either retrospectively or in near-real time. For flood emergency response, remote-sensing-based flood mapping is highly valuable as it can offer continued observational information about the flood extent over large geographical domains. Information about the floodwater depth across the inundated domain is important for damage assessment, rescue, and prioritizing of relief resource allocation, but cannot be readily estimated from remote sensing analysis. The Floodwater Depth Estimation Tool (FwDET) was developed to augment remote sensing analysis by calculating water depth based solely on an inundation map with an associated digital elevation model (DEM). The tool was shown to be accurate and was used in flood response activations by the Global Flood Partnership. Here we present a new version of the tool, FwDET v2.0, which enables water depth estimation for coastal flooding. FwDET v2.0 features a new flood boundary identification scheme which accounts for the lack of confinement of coastal flood domains at the shoreline. A new algorithm is used to calculate the local floodwater elevation for each cell, which improves the tool's runtime by a factor of 15 and alleviates inaccurate local boundary assignment across permanent water bodies. FwDET v2.0 is evaluated against physically based hydrody-namic simulations in both riverine and coastal case studies. The results show good correspondence, with an average difference of 0.18 and 0.31 m for the coastal (using a 1 m DEM) and riverine (using a 10 m DEM) case studies, respectively. A FwDET v2.0 application of using remote-sensing-derived flood maps is presented for three case studies. These case studies showcase FwDET v2.0 ability to efficiently provide a synoptic assessment of floodwater. Limitations include challenges in obtaining high-resolution DEMs and increases in uncertainty when applied for highly fragmented flood inundation domains.

A comprehensive flood inundation mapping for Hurricane Harvey using an integrated hydrological and hydraulic model

“…Outside the United States, the CREST was coupled with an 1D fully distributed linear reservoir routing scheme and found success over a study in China (Shen et al 2017). The National Water Center led an effort to integrate the WRF-Hydro hydrologic model and the Height Above Nearest Datum (HAND) inundation mapping method into the new National Water Model (NWM; Cohen et al 2018). The HAND method performed a simulation of a 2016 Texas flooding event with good agreement with remote sensing observations and less computation cost (Zhang et al 2018).…”

Flood hazard mapping for data-scarce and ungauged coastal river basins using advanced hydrodynamic models, high temporal-spatial resolution remote sensing precipitation data, and satellite imageries

“…The Science Toolbox Exploitation Platform (SNAP) Toolkit developed by ESA was applied to derive the high-resolution flood inundation extent from Sentinel-1 SAR (Mcvittie 2019). The Floodwater Depth Estimation Tool (FwDET) developed as part of the National Aeronautics and Space Administration (NASA) Applied Sciences Mid-Atlantic Communities and Areas at Intensive Risk demonstration project was employed to achieve flood inundation depths (Cohen et al , 2019.…”

“…We believe that estimating inundation depths from an inundation map derived from satellite imageries with an associated digital elevation model will support the model calibration and verification processes in data-scarce and ungauged river basins. However, major limitations include obtaining accurate high-resolution DEMs and dealing with fragmented flood inundation domains (Cohen et al 2019).…”

“…Along with the development of mathematical models, the growing availability of distributed remote sensing data with high-resolution and free-of-charge sources, as well as increased computational resources, has reinforced the capability and opportunities for flood inundation modeling. Thus, remote sensing-based analysis of flooding can be implemented rapidly in near real-time and in large-scale applications (Cohen et al 2019). More recently, many studies have been conducted to utilize satellite-derived data such as satellite precipitation and satellite imagery to enhance model performances of flood inundation.…”

Compound Effects of Flood Drivers and Wetland Elevation Correction on Coastal Flood Hazard Assessment

“…Digital elevation models (DEMs) are key input data for physically based modeling and flood hazard mapping either with static bathub projections (Cohen et al, 2019; Poulter & Halpin, 2008; Strauss et al, 2012) or hydrodynamic modeling based on the shallow‐water equations (Bakhtyar et al, 2018; Ferreira et al, 2014; Gallien et al, 2014). Several studies, however, have reported limitations of DEMs to represent terrain features including hydraulically important infrastructure (Gallien et al, 2018; Néelz et al, 2006) and high vertical bias that might triple estimates of global vulnerability to sea level rise and coastal flooding (Kulp & Strauss, 2019).…”